Research On Evaluation Of Individual Credit Risk In Commercial Banks Of China

Due to the rapid development of the consumer credit industry which has the features of'high risk high return, low risk low return', the financial institutions have to face tremendous credit risk while they pursue higher profit. Therefore, avoiding individual credit risk becomes an important problem for banks and crediting organizations. Before granting credit loans, banks need to make scientifically credit evaluation of credit consumer, which contains objective and accurate assessment of ability and willingness to pay, so that they can control and reduce loss on bad debt. As a famous parametric pattern based on statistic theory and computer science, logistic regression method has been applied widely in personal credit scoring field. This thesis designs the target system of individual credit scoring by using consumer credit data of a commercial bank in Beijing and logistic return method. This paper finds nine variables which has significant link to returning loans and eventually establishes an individual credit scoring model by using Forward-conditional and Enter method in SPSS and analyze applicability of model. At last, the article discusses the operation of the individual credit scoring model in consumer credit industry, points out the possible problems and solutions on the practice of individual credit scoring model.